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Standard and novel imaging methods for multiple myeloma: correlates with prognostic laboratory variables including gene expression profiling data.

ABSTRACT: Multiple myeloma causes major morbidity resulting from osteolytic lesions that can be detected by metastatic bone surveys. Magnetic resonance imaging and positron emission tomography can detect bone marrow focal lesions long before development of osteolytic lesions. Using data from patients enrolled in Total Therapy 3 for newly diagnosed myeloma (n=303), we analyzed associations of these imaging techniques with baseline standard laboratory variables assessed before initiating treatment. Of 270 patients with complete imaging data, 245 also had gene expression profiling data. Osteolytic lesions detected on metastatic bone surveys correlated with focal lesions detected by magnetic resonance imaging and positron emission tomography, although, in two-way comparisons, focal lesion counts based on both magnetic resonance imaging and positron emission tomography tended to be greater than those based on metastatic bone survey. Higher numbers of focal lesions detected by magnetic resonance imaging and positron emission tomography were positively linked to high serum concentrations of C-reactive protein, gene-expression-profiling-defined high risk, and the proliferation molecular subgroup. Positron emission tomography focal lesion maximum standardized unit values were significantly correlated with gene-expression-profiling-defined high risk and higher numbers of focal lesions detected by positron emission tomography. Interestingly, four genes associated with high-risk disease (related to cell cycle and metabolism) were linked to counts of focal lesions detected by magnetic resonance imaging and positron emission tomography. Collectively, our results demonstrate significant associations of all three imaging techniques with tumor burden and, especially, disease aggressiveness captured by gene-expression-profiling-risk designation. (Clinicaltrials.gov identifier: NCT00081939).

SUBMITTER: Waheed S

PROVIDER: S-EPMC3533662 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature

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Standard and novel imaging methods for multiple myeloma: correlates with prognostic laboratory variables including gene expression profiling data.

Waheed Sarah S Mitchell Alan A Usmani Saad S Epstein Joshua J Yaccoby Shmuel S Nair Bijay B van Hemert Rudy R Angtuaco Edgardo E Brown Tracy T Bartel Twyla T McDonald James J Anaissie Elias E van Rhee Frits F Crowley John J Barlogie Bart B

Haematologica 20120624 1

Multiple myeloma causes major morbidity resulting from osteolytic lesions that can be detected by metastatic bone surveys. Magnetic resonance imaging and positron emission tomography can detect bone marrow focal lesions long before development of osteolytic lesions. Using data from patients enrolled in Total Therapy 3 for newly diagnosed myeloma (n=303), we analyzed associations of these imaging techniques with baseline standard laboratory variables assessed before initiating treatment. Of 270 p ...[more]

PMID: 22733020

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Project description:PurposePhase analysis can assess left ventricular dyssynchrony. The independent prognostic value of phase variables over positron emission tomography myocardial perfusion imaging (PET-MPI) variables including myocardial flow reserve (MFR) has not been studied. The aim of this study was to explore the prognostic value of phase variables for predicting mortality over standard PET-MPI variables.MethodsConsecutive patients who underwent pharmacological stress-rest 82Rb PET study were enrolled. All PET-MPI variables including phase variables (phase entropy, phase bandwidth, and phase standard deviation) were automatically obtained by QPET software (Cedars-Sinai, Los Angeles, CA). Cox proportional hazard analyses were used to assess associations with all-cause mortality (ACM).ResultsIn a total of 3963 patients (median age 71 years; 57% male), 923 patients (23%) died during a median follow-up of 5 years. Annualized mortality rates increased with stress phase entropy, with a 4.6-fold difference between the lowest and highest decile groups of entropy (2.6 vs. 12.0%/year). Abnormal stress phase entropy (optimal cutoff value, 43.8%) stratified ACM risk in patients with normal and impaired MFR (both p < 0.001). Among three phase variables, only stress phase entropy was significantly associated with ACM after the adjustment of standard clinical and PET-MPI variables including MFR and stress-rest change of phase variables, whether modeled as binary variables (adjusted hazard ratio, 1.44 for abnormal entropy [> 43.8%]; 95%CI, 1.18-1.75; p < 0.001) or continuous variables (adjusted hazard ratio, 1.05 per 5% increase; 95%CI, 1.01-1.10; p = 0.030). The addition of stress phase entropy to the standard PET-MPI variables significantly improved the discriminatory power for ACM prediction (p < 0.001), but the other phase variables did not (p > 0.1).ConclusionStress phase entropy is independently and incrementally associated with ACM beyond standard PET-MPI variables including MFR. Phase entropy can be obtained automatically and included in clinical reporting of PET-MPI studies to improve patient risk prediction.

Dataset Information

Standard and novel imaging methods for multiple myeloma: correlates with prognostic laboratory variables including gene expression profiling data.

Publications

Standard and novel imaging methods for multiple myeloma: correlates with prognostic laboratory variables including gene expression profiling data.

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